Embracing Imperfection: The 3-Month Rule in Software Development
In the world of engineering, it’s often said that starting small and learning along the way is the key to success. This philosophy aligns perfectly with Paul Graham’s advice: “Do things that don’t scale.” But how does one practically apply this concept in the realm of coding and software development?
After dedicating the last eight months to developing my AI podcast platform, I’ve formulated a straightforward framework: every unscalable solution I implement is allowed a three-month trial. At the end of this period, these approaches must either demonstrate their effectiveness and be expanded upon, or they will be discarded.
The startup Mindset: Dismissing Scalability
It’s common for engineers to be preoccupied with creating scalable solutions from the outset. We often become enamored with concepts like microservices and distributed systems, envisioning architectures that can support millions of users. However, in a startup environment, this focus on scale can lead to expensive delays. Frequently, we wind up optimizing for future users who haven’t even arrived yet, while ignoring the current needs of our existing user base.
My three-month rule encourages me to embrace simplicity. By prioritizing straightforward, albeit imperfect solutions, I’m able to launch products that directly meet user needs, all while gathering valuable insights along the way.
Current Infrastructure Strategies: Smart Unscalability
1. Consolidation: Everything on One Virtual Machine
With my entire stack—including the database, web server, and background jobs—running on a single, affordable virtual machine, I’ve opted for simplicity over redundancy. While this may seem reckless, it’s proven invaluable. In just two months, I have come to understand my actual resource requirements far better than any formal capacity planning ever could. My application, which I initially presumed to be “AI-heavy,” only peaks at 4GB of RAM usage. Avoiding a complex Kubernetes setup has spared me from managing unnecessary resources.
2. Hardcoded Configuration for Efficiency
Rather than dealing with configuration files and environment variables, I’ve chosen to hardcode essential values, such as pricing tiers and the maximum number of users, directly into my codebase. While it might seem primitive, this approach allows me to quickly retrieve configuration data and maintain a clear record of changes in my version history. In three months, I’ve only needed to modify these values three times, saving me substantially in development time.
